Imagine a drone that can fly into a dangerous chemical plant, land precisely on a pipe, and release a tiny robotic crawler to check for rust under the insulation. It uses a smart 'brain' and augmented reality glasses to help workers monitor everything from a safe distance. This keeps people away from hazardous areas while still getting a detailed X-ray of the equipment.
Workers in petrochemical plants are exposed to dangerous environments when inspecting insulated pipes for corrosion. Current methods are high-risk and mentally stressful for the personnel involved.
A modular robotic system combining an aerial drone for navigation and light-weight crawlers equipped with X-ray or Pulsed Eddy-Current sensors. It includes an AI-driven analysis layer and an Augmented Reality interface for remote worker support.
If you are a refinery operator dealing with corrosion in insulated piping—this project developed a hybrid aerial-crawler robot that uses X-ray and PEC sensors to inspect pipes. This keeps workers in safe zones and reduces their stress levels.
If you are a plant manager dealing with hazardous inspection environments—this project developed a modular robotic system that combines flying and crawling locomotion. It allows for complete inspections of cluttered locations without putting staff at risk.
If you are an inspection firm dealing with high-risk pipe audits—this project developed a system integrating AI and Augmented Reality to reduce human workload. It provides a way to perform TRL7 validated inspections in operational facilities.
Based on available project data, the specific commercial price of the robot is not listed, though the EU provided a contribution of EUR 2,999,725 for development.
The project aimed for TRL7 validation and demonstration in a real operational petrochemical facility, indicating it is designed for industrial environments.
Based on available project data, specific licensing terms are not provided, but the consortium includes 4 industry partners and 3 SMEs who likely share the intellectual property.
The system integrates AI for understanding and Augmented Reality to support workers, reducing their workload and stress during maintenance tasks.
The project period runs from 2022-09-01 to 2025-08-31, with the final phase focusing on demonstration in an operational facility.
The consortium is heavily industry-driven with a 57% industry ratio, comprising 4 industrial partners and 3 SMEs. The presence of major end-users like BASF and Chevron suggests the technology is being developed for direct commercial application in the petrochemical sector rather than pure academic research.
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